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Motivating users to self-disclose online is significant to the long-term development of social media. Therefore, research on emotional disclosure, a significant form of self-disclosure, is required. By developing a stimulus-organism-response model, this study aims to investigate the mechanisms by which the social media environment affects users' online emotional disclosure.

This paper proposes two dimensions of social media environments, the online interpersonal environment (tie strength and network size) and the online information environment (self-reference). They are hypothesized to stimulate users' internal psychological needs (image management and emotional expression) which in turn will influence their emotional disclosure intentions. Using data from 489 users of WeChat Moments, the authors conduct partial least squares analysis to validate the research model.

The findings show that users' intrinsic psychological needs are stimulated by social media environments, but network size is not correlated with the need for emotional expression. The user's need for emotional expression promotes both positive and negative emotional disclosure intentions. The need for image management has a positive impact on positive emotion disclosure intentions but has a negative impact on negative emotion disclosure intentions.

This study contributes to the understanding of online emotional disclosure. It can also help social media managers create efficient plans to encourage users to create content.

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-04-2022-0245.

This study discusses the tracking trajectory issue of the exoskeleton under the bounded disturbance and designs an useful tracking trajectory control method to solve it. By using the proposed control method, the tracking error can be successfully convergence to the assigned boundary. Meanwhile, the chattering effect caused by the actuators is already reduced, and the tracking performance of the pneumatic artificial muscles (PAMs) elbow exoskeleton is improved effectively.

A prescribed performance sliding mode control method was developed in this study to fulfill the joint position tracking trajectory task on the elbow exoskeleton driven by two PAMs. In terms of the control structure, a dynamic model was built by conforming to the adaptive law to compensate for the time variety and uncertainty exhibited by the system. Subsequently, a super-twisting algorithm-based second-order sliding mode control method was subjected to the exoskeleton under the boundedness of external disturbance. Moreover, the prescribed performance control method exhibits a smooth prescribed function with an error transformation function to ensure the tracking error can be finally convergent to the pre-designed requirement.

From the theoretical perspective, the stability of the control method was verified through Lyapunov synthesis. On that basis, the tracking performance of the proposed control method was confirmed through the simulation and the manikin model experiment.

As revealed by the results of this study, the proposed control method sufficiently applies to the PAMs elbow exoskeleton for tracking trajectory, which means it has potential application in the actual robot-assisted passive rehabilitation tasks.

We aim to clarify the effect of economic uncertainty on Chinese stock market fluctuations. We extend the understanding of the asymmetric connectedness between economic uncertainty and stock market risk and provide different characteristics of spillovers from economic uncertainty to both upside and downside risk. Furthermore, we aim to provide the different impact patterns of stock market volatility following several exogenous shocks.

We construct a Chinese economic uncertainty index using a Factor-Augmented Variable Auto-Regressive Stochastic Volatility (FAVAR-SV) model for high-dimensional data. We then examine the asymmetric impact of realized volatility and economic uncertainty on the long-term volatility components of the stock market through the asymmetric Generalized Autoregressive Conditional Heteroskedasticity-Mixed Data Sampling (GARCH-MIDAS) model.

Negative news, including negative return-related volatility and higher economic uncertainty, has a greater impact on the long-term volatility components than positive news. During the financial crisis of 2008, economic uncertainty and realized volatility had a significant impact on long-term volatility components but did not constitute long-term volatility components during the 2015 A-share stock market crash and the 2020 COVID-19 pandemic. The two-factor asymmetric GARCH-MIDAS model outperformed the other two models in terms of explanatory power, fitting ability and out-of-sample forecasting ability for the long-term volatility component.

Many GARCH series models can also combine the GARCH series model with the MIDAS method, including but not limited to Exponential GARCH (EGARCH) and Threshold GARCH (TGARCH). These diverse models may exhibit distinct reactions to economic uncertainty. Consequently, further research should be undertaken to juxtapose alternative models for assessing the stock market response.

Our conclusions have important implications for stakeholders, including policymakers, market regulators and investors, to promote market stability. Understanding the asymmetric shock arising from economic uncertainty on volatility enables market participants to assess the potential repercussions of negative news, engage in timely and effective volatility prediction, implement risk management strategies and offer a reference for financial regulators to preemptively address and mitigate systemic financial risks.

First, in the face of domestic and international uncertainties and challenges, policymakers must increase communication with the market and improve policy transparency to effectively guide market expectations. Second, stock market authorities should improve the basic regulatory system of the capital market and optimize investor structure. Third, investors should gradually shift to long-term value investment concepts and jointly promote market stability.

This study offers a novel perspective on incorporating a Chinese economic uncertainty index constructed by a high-dimensional FAVAR-SV model into the asymmetric GARCH-MIDAS model.

Most of the linear encoders are based on optics. The accuracy and reliability of these encoders are greatly reduced in polluted and noisy environments. Moreover, these encoders have a complex structure and large sensor volume and are thus not suited to small application scenarios and do not have universality. This paper aims to present a new absolute magnetic linear encoder, which has a simple structure, small size and wide application range.

The effect of swing error is analyzed for the sensor structural arrangement. A double-threshold interval algorithm is then proposed to synthesize multiple interval electrical angles into absolute angles and convert them into actual displacement distances.

The final linear encoder measurement range is 15.57 mm, and the resolution reaches ± 2 µm. The effectiveness of the algorithm is demonstrated experimentally.

The linear encoder has good robustness, and high measurement accuracy, which is suitable for industrial production. The linear encoder has been mass-produced and used in an electric power-assisted braking system.

Artificial intelligence (AI) is transforming consumers' experiences and how firms identify, create, nurture and manage interactive marketing relationships. However, most marketers do not have a clear understanding of what AI is and how it may mutually benefit consumers and firms. In this paper, the authors conduct an extensive review of the marketing literature, develop an AI framework for understanding value co-creation in interactive buyer–seller marketing relationships, identify research gaps and offer a future research agenda.

The authors first conduct an extensive literature review in 16 top marketing journals on AI. Based on this review, an AI framework for understanding value co-creation in interactive buyer–seller marketing relationships was conceptualized.

The literature review led to a number of key research findings and summary areas: (1) an historical perspective, (2) definitions and boundaries of AI, (3) AI and interactive marketing, (4) relevant theories in the domain of interactive marketing and (5) synthesizing AI research based on antecedents to AI usage, interactive AI usage contexts and AI-enabled value co-creation outcomes.

This is one of the most extensive reviews of AI literature in marketing, including an evaluation of in excess or 300 conceptual and empirical research. Based on the findings, the authors offer a future research agenda, including a visual titled “What is AI in Interactive Marketing? AI design factors, AI core elements & interactive marketing AI usage contexts.”

This paper aims to study the effect of ultraviolet (UV) light on the corrosion behavior of BC550 weathering steel in simulated marine atmospheric environment.

The effect of UV light on the corrosion behavior of BC550 weathering steel in simulated marine atmospheric environments were investigated by the corrosion weight gain experiment, in situ electrochemical noise, scanning electron microscope and X-ray diffraction.

UV light accelerated the corrosion process of BC550 weathering steel in the simulated marine atmospheric environment during the first 168 h. The maximum influence factor of UV light was 0.32, and it was only 0.08 after 168 h of corrosion process.

As the extension of corrosion time, the thickness and density of the corrosion product layer increased, which weakened the acceleration effect of UV light.

This study aims to investigate the external effect of the economic growth target pressure of local governments on establishment-level SO₂ emissions.

Based on manually collected panel data of 74,058 China's industrial establishments and more than 330 thousand observations from CIED and ESR, the authors use a firm-fixed effect model, instrumental variables estimation and heterogeneity tests to identify the environmental externality of economic growth target pressure.

The establishments in cities that meet or slightly exceed the economic growth target experience greater negative externality measured by SO₂ emission intensity. This external effect is more pronounced in regions: with a strict and overweighted target setting; with stronger officials' promotion incentives; with a low degree of marketization; and in firms with great economic importance. The authors identify the underlying mechanisms of dependence on dirty industry and the relaxation of environmental enforcement. And the environmental protection constraints in 2007 mitigate the negative externality.

The paper sheds light on to what extent economic growth target pressure has a negative externality of pollution in China and how this pressure may conflict with environmental protection.

This paper complements prior research on the economic effects of economic growth targets, expands the knowledge on the determinants of establishment-level pollution emission from the perspective of target pressure and provides insight into the environmental externality that results from political factors.

The manufacturing investment shift from developed countries to emerging and developing regions creates further needs for identifying appropriate green certification strategies. This study proposes that alignments between green certification practices (GCRs) and process innovation (PIN) could help identify appropriate strategies that national economic development can influence.

Drawing on the diffusion of innovation theories, this study proposed a taxonomy to examine whether sustainable performance differs depending on the levels of alignment and the role of national economic development. The study uses an empirical survey approach to highlight alignments between GCRs and PIN among developed, developing and emerging economic nations, addressing resource allocation for the world's sustainable development goals (SDGs).

Manufacturers need to align PIN practices with the level of green certification to achieve sustainable performance. Manufacturers experiencing higher payoffs from various improvements successfully align in GCR and PIN. The alignment between these two concepts can derive different taxonomies, which highlight performance and managerial implications for manufacturers. The manufacturers followed three distinct typologies: minimalist, process active and proactive. Besides, building on the theory of performance frontiers, the findings indicated that manufacturers in developing and emerging economies placed the most substantial GCR effort compared to their counterparts in developed nations. Manufacturers in developed countries are increasingly reaching the “diminishing points” and investing limited resources in GCR just enough to keep their competitive positioning as order qualifiers rather than order winners. Developing economies are catching up very quickly in attaining GCRs and business performance.

This insight is essential for managers to adapt to nations' economic development conditions and appropriately and effectively align resources.

The findings offer a decision-making process and provide straightforward guidelines for supply chain managers' green certification adoption.

In including both PIN and green certification, this paper adds greater comprehensiveness and richness to the supply chain literature.

This study aims to analyze the importance and performance of customer-facing technologies in luxury hotels. The study also assessed differences between and within the four generations in the importance-performance analysis (IPA).

Data were collected using a Qualtrics panel of recent luxury hotel customers in the USA belonging to all four generations. The cross-generational IPA was conducted using t-tests and (ANAOVA).

The IPA matrix concentrated most technology items in either low importance – low performance or high importance – high performance quadrants. One-way ANOVA revealed significant differences between generations on the importance ratings of all technology items except wireless charging power solutions and on the performance ratings of all technology items. Furthermore, post hoc tests indicated that millennials rated luxury technology most favorably among the four cohorts, followed by generations Z, X and Baby Boomers. In addition, significant differences between the importance and performance of many technology items within each generational cohort were observed. Overall, Wi-Fi was unanimously ranked across generations as the most important technology among luxury guests, but it was the only one that scored lower in performance than importance.

The findings of this study contribute to hospitality scholarship in two primary ways: the importance and performance of technology and generational differences. The results advance the understanding of the impact of generational factors on customer-facing technological adoptions in the luxury hotel sector.

Technologies that are pervasive in the home also become vital offerings for hotels. The more pervasive technology, the more a luxury hotel must work to ensure that it performs at optimal levels. Additionally, which technologies are most important to targeted generations are provided so practitioners may budget for their implementation.

This research is a pivotal step forward in unraveling the intricate interplay between generational factors and technological evaluations, providing a foundation for future research and practical applications in a rapidly evolving technological landscape in the hospitality industry.